Examination of Triacylglycerol Biosynthetic Pathways via De Novo Transcriptomic and Proteomic Analyses in an Unsequenced Microalga

Abstract

Biofuels derived from algal lipids represent an opportunity to dramatically impact the global energy demand for transportation fuels. Systems biology analyses of oleaginous algae could greatly accelerate the commercialization of algal-derived biofuels by elucidating the key components involved in lipid productivity and leading to the initiation of hypothesis-driven strain-improvement strategies. However, higher-level systems biology analyses, such as transcriptomics and proteomics, are highly dependent upon available genomic sequence data, and the lack of these data has hindered the pursuit of such analyses for many oleaginous microalgae. In order to examine the triacylglycerol biosynthetic pathway in the unsequenced oleaginous microalga, Chlorella vulgaris, we have established a strategy with which to bypass the necessity for genomic sequence information by using the transcriptome as a guide. Our results indicate an upregulation of both fatty acid and triacylglycerol biosynthetic machinery under oil-accumulating conditions, and demonstrate the utility of a de novo assembled transcriptome as a search model for proteomic analysis of an unsequenced microalga.

RNA-Seq and metabolic flux analysis of Tetraselmis sp. M8 during nitrogen starvation reveals a two-stage lipid accumulation mechanism

“…M8, particularly for DGAT that exhibited reduced expression during nitrogen-starvation. Post-transcriptional control of DGAT has been reported in proteomics studies of Chlorella vulgaris (Guarnieri et al, 2011) and Brassica napus (Nykiforuk et al, 2002), and has also been suggested for Neochloris oleoabundans (Rismani-Yazdi et al, 2012). The evidence for posttranscriptional control of DGAT is further supported by the lack of the phospholipid:diacylglycerol acyltransferase (PDAT) gene within the Tetraselmis sp.…”

“…Currently, algal strain development remains one of the most important aspects of microalgae-for-biofuel Sun et al, 2013). In most studies, the focus has been on metabolic pathway reconstruction and gene discovery at a single time-point, usually 48 to 96 h into starvation phase when lipid accumulation is at its peak (Guarnieri et al, 2011; Rismani-Yazdi et al, 2012; Sun et al, 2013). While this approach successfully allowed for the reconstruction of fatty acid (FA), triacylglyceride (TAG), β-oxidation and other metabolic pathways, the limited scope of these studies restricts our understanding how the expression of these pathways change, particularly during early stationary phase as cells transition from growth phase into starvation phase.…”

Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions

“…The lipids produced by C. vulgaris can be grouped in the esters: triacylglycerol (TAG), phosphatidylglycerol (PG), phosphatidylinositol (PI), phosphatidylethanolamine (PE), sulfoquinovosyldiglycerol, monogalactosyldiglycerol (MGDG), digalactosyldiglycerol, and phosphatidylcholine, where TAG can accumulate to 20% to 60% of dry cell weight (Guarnieri et al, 2011(Guarnieri et al, , 2013Bellou et al, 2014).…”

“…RNA sequencing data and literature data such as specific CO 2 and Glc consumption rates were used to constrain the model under growth conditions in the light and dark (Guarnieri et al, 2011). For each growth condition, the storage and consumption of starch were taken into account; we calculated the rates using experimental data (Supplemental Table S6).…”

“…Model benchmarking on carbon and nitrogen sources was performed using Biolog plates PM1 to PM3, following the previously reported protocol described by Chaiboonchoe et al (2014), with the following modifications. C. vulgaris was grown to midlog phase in modified BBM (Guarnieri et al, 2011), pelleted via centrifugation at 4,000g for 5 min, washed, and resuspended in fresh medium to a final optical density of 0.1 (nitrate was excluded for nitrogen phenotyping). Aliquots of 100 mL were inoculated onto Biolog plates and examined for 96 h in the plate reader with readings every 15 min.…”